The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
The Generative AI Landscape in Education: Mapping the Terrain of Opportunities, Challenges, and Student Perception
Open accessAbstract
Generative AI (GAI) technologies like ChatGPT are permanently changing academic education. Their integration opens up vast opportunities for bespoke learning and better student interaction but also brings about academic honesty issues and the application of real-life educators. This study aims to fill the literature gap regarding the use of multiple GAI tools and their effect on academic outcomes via a comprehensive review. A systematic literature review was performed following PRISMA guidelines to synthesize results on the potential and drawbacks of GAI in educational domains. We included theoretical and empirical papers that used qualitative, quantitative, or mixed-methods study designs. We have also explored conceptual frameworks and the most creative AI applications with a special emphasis on uniqueness and practicability. Experiences, and Perceptions Concerning To compile the information needed we gathered insights into what students were going through by conducting the survey which contains 200 respondents of undergraduate university students gathering insights into the college students’ experiences and perceptions related to GAI used for educational purposes. At the basic level, GAI comprises areas like personalization, task automation, teacher assistance, and efficiency among others, and respective solutions for the immersion of a learner in learning processes to reform directions. However, it generates plenty of challenges such as the question of assessment integrity, the risk that too much automated grading could overwhelm educational value, and relevantly the veracity of AI-generated content as well as the potential disruption to skills like critical thinking, in addition to data privacy and ethical issues. Student Perception Survey the text also indicates that most students, as per the student perception survey found AI systems useful in academic support. However, they also know the other side of the coin and are very familiar with the technology constraints and challenges.
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In the citing paper
“Studies have revealed that traditional plagiarism detection tools, such as Turnitin, are ineffective in identifying AI-gen -erated content, often yielding false positives or negatives [ 31, 60, 85, 89, 90 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [60]
In the citing paper
“The reliance on AI for tasks requiring cognitive engagement results in declining independent reasoning, writing abilities, critical thinking, and analytical skills, making students less prepared for realworld problem-solving scenarios [ 60, 72, 93, 97, 98].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [60]
Citations
Cites
1 retracted
Yu, H. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e24289 · Cited by 225 · cited 3×
“This transformation improves operational efficiency and contributes to creating a more adaptable and digital educational environment [50].”
BackgroundRetractedThe PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · International Journal of Surgery · doi:10.1016/j.ijsu.2021.105906 · Cited by 11,748
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 4×
“It also promotes innovative teaching methods by introducing novel pedagogical strategies that leverage GAI capabilities [2].”
BackgroundMethodInfluentialBAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · cited 2×
“The guidelines should cover topics such as data privacy and security, algorithmic bias mitigation, transparency and accountability in GAI systems, and ethical considerations in developing and deploying AI technologies [7], [26], [61].”
BackgroundChatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079
Baidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004 · cited 4×
“A key area of impact highlighted in recent research is the generation of prompts for formative assessment activities, which is instrumental in fostering personalized and interactive learning environments [6], [24], [25].”
BackgroundMethodInfluentialStudents' voices on generative ai: perceptions, benefits, and challenges in higher education
Chan, C. K. Y., & Hu, W. (2023) · arXiv · doi:10.48550/arxiv.2305.00290 · Cited by 2,504
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Cited by
Sorted by citations
Shen, M., Shen, Y., Liu, F., & Jin, J. (2025) · BMC Nursing · doi:10.1186/s12912-025-03115-8 · Cited by 76
“Both participants expressed skepticism regarding GenAI accuracy and completeness, frequently revising and refining their prompts to improve response quality [33].”
Metaverse for Education: Developments, Challenges, and Future Direction
Chamola, V., Peelam, M. S., Mittal, U., Hassija, V., Singh, A., Pareek, R., Mangal, P., Sangwan, D., de Albuquerque, V. H. C., Mahmud, M., et al. (2025) · Computer Applications in Engineering Education · doi:10.1002/cae.70018 · Cited by 87
“GAI ‐ driven personalization in the Metaverse for education represents a revolutionary shift in how learning experiences are customized to individual needs and preferences [216, 217].”
A Meta‐Analysis of the Impact of Generative Artificial Intelligence on Learning Outcomes
Ma, N., & Zhong, Z. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70117 · Cited by 62
Dui, H., Zeng, Q., & Xie, M. (2025) · Frontiers of Engineering Management · doi:10.1007/s42524-025-4147-6 · Cited by 39
“Ahmed Z et al. (2024) used generative AI to assist teaching and promote learning equity.”
ChatGPT as a cognitive crutch: Evidence from a randomized controlled trial on knowledge retention
Barcaui, A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102287 · Cited by 51
Metadata
- Authors
- Ahmed, Z., Shanto, S. S., Rime, M. H. K., Morol, M. K., Fahad, N., Hossen, M. J., & Abdullah-Al-Jubair, M.
- Affiliations
- American International University-Bangladesh (BD)
- University of Rajshahi (BD)
- Multimedia University (MY)
- ORCID
- Venue
- IEEE Access
- Published
- 2024
- Volume
- 12
- Pages
- 147023-147050
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W4402772412
- Cited by
- 123
- References
- 96
- Citations by year
- 2026: 57 · 2025: 61 · 2024: 5
- FWCI
- 46.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- IEEE Access (publishedVersion, cc-by-nc-nd)
- Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI in education, ChatGPT, student perceptions, academic integrity, automated grading, AI-generated content, personalized learning, critical thinking, data privacy, AI ethics, undergraduate students, academic support
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